On the Identifiability of Transmission Dynamic Models for Infectious Diseases

Understanding the transmission dynamics of infectious diseases is important for both biological research and public health applications. It has been widely demonstrated that statistical modeling provides a firm basis for inferring relevant epidemiological quantities from incidence and molecular data. However, the complexity of transmission dynamic models presents two challenges: (1) the likelihood function of the models is generally not computable, and computationally intensive simulation-based inference methods need to be employed, and (2) the model may not be fully identifiable from the available data. While the first difficulty can be tackled by computational and algorithmic advances, the second obstacle is more fundamental. Identifiability issues may lead to inferences that are driven more by prior assumptions than by the data themselves. We consider a popular and relatively simple yet analytically intractable model for the spread of tuberculosis based on classical IS6110 fingerprinting data. We report on the identifiability of the model, also presenting some methodological advances regarding the inference. Using likelihood approximations, we show that the reproductive value cannot be identified from the data available and that the posterior distributions obtained in previous work have likely been substantially dominated by the assumed prior distribution. Further, we show that the inferences are influenced by the assumed infectious population size, which generally has been kept fixed in previous work. We demonstrate that the infectious population size can be inferred if the remaining epidemiological parameters are already known with sufficient precision.     

Two-Stage Processing of Sounds Explains Behavioral Performance Variations due to Changes in Stimulus Contrast and Selective Attention: An MEG Study

Selectively attending to task-relevant sounds whilst ignoring background noise is one of the most amazing feats performed by the human brain. Here, we studied the underlying neural mechanisms by recording magnetoencephalographic (MEG) responses of 14 healthy human subjects while they performed a near-threshold auditory discrimination task vs. a visual control task of similar difficulty. The auditory stimuli consisted of notch-filtered continuous noise masker sounds, and of 1020-Hz target tones occasionally () replacing 1000-Hz standard tones of 300-ms duration that were embedded at the center of the notches, the widths of which were parametrically varied. As a control for masker effects, tone-evoked responses were additionally recorded without masker sound. Selective attention to tones significantly increased the amplitude of the onset M100 response at 100 ms to the standard tones during presence of the masker sounds especially with notches narrower than the critical band. Further, attention modulated sustained response most clearly at 300–400 ms time range from sound onset, with narrower notches than in case of the M100, thus selectively reducing the masker-induced suppression of the tone-evoked response. Our results show evidence of a multiple-stage filtering mechanism of sensory input in the human auditory cortex: 1) one at early (100 ms) latencies bilaterally in posterior parts of the secondary auditory areas, and 2) adaptive filtering of attended sounds from task-irrelevant background masker at longer latency (300 ms) in more medial auditory cortical regions, predominantly in the left hemisphere, enhancing processing of near-threshold sounds.     

Ecological inference on bacterial succession using curve-based community fingerprint data analysis, demonstrated with rhizoremediation experiment

Nucleic acid-based community fingerprinting methods are valuable tools in microbial ecology, as they offer rapid and robust means to compare large series of replicates and references. To avoid the time-consuming and potentially subjective procedures of peak-based examination, we assessed the possibility to apply direct curve-based data analysis on community fingerprints produced with bacterial length heterogeneity PCR (LH-PCR). The dataset comprised 180 profiles from a 21-week rhizoremediation greenhouse experiment with three treatments and 10 sampling times. Curve-based analysis quantified the progressive effect of the plant (Galega orientalis) and the reversible effect of the contaminant (fuel oil) on bacterial succession. The major observed community shifts were assigned to changes in plant biomass and contamination level by canonical correlation analysis. A novel method to extract relative abundance data from the fingerprint curves for Shannon diversity index revealed contamination to reversibly decrease community complexity. By cloning and sequencing the fragment lengths, recognized to change in time in the averaged LH-PCR profiles, we identified Aquabacterium (Betaproteobacteria) as the putative r-strategic fuel oil degrader, and K-strategic Alphaproteobacteria growing in abundance later in succession. Curve-based community fingerprint analysis can be used for rapid data prescreening or as a robust alternative for the more heavily parameterized peak-based analysis.     

Construction of chimeric dual-chain avidin by tandem fusion of the related avidins

Background

Avidin is a chicken egg-white protein with high affinity to vitamin H, also known as D-biotin. Many applications in life science research are based on this strong interaction. Avidin is a homotetrameric protein, which promotes its modification to symmetrical entities. Dual-chain avidin, a genetically engineered avidin form, has two circularly permuted chicken avidin monomers that are tandem-fused into one polypeptide chain. This form of avidin enables independent modification of the two domains, including the two biotin-binding pockets; however, decreased yields in protein production, compared to wt avidin, and complicated genetic manipulation of two highly similar DNA sequences in the tandem gene have limited the use of dual-chain avidin in biotechnological applications.

Principal Findings

To overcome challenges associated with the original dual-chain avidin, we developed chimeric dual-chain avidin, which is a tandem fusion of avidin and avidin-related protein 4 (AVR4), another member of the chicken avidin gene family. We observed an increase in protein production and better thermal stability, compared with the original dual-chain avidin. Additionally, PCR amplification of the hybrid gene was more efficient, thus enabling more convenient and straightforward modification of the dual-chain avidin. When studied closer, the generated chimeric dual-chain avidin showed biphasic biotin dissociation.

Significance

The improved dual-chain avidin introduced here increases its potential for future applications. This molecule offers a valuable base for developing bi-functional avidin tools for bioseparation, carrier proteins, and nanoscale adapters. Additionally, this strategy could be helpful when generating hetero-oligomers from other oligomeric proteins with high structural similarity.     

Analysis of forward and backward Second Harmonic Generation images to probe the nanoscale structure of collagen within bone and cartilage

Collagen ultrastructure plays a central role in the function of a wide range of connective tissues. Studying collagen structure at the microscopic scale is therefore of considerable interest to understand the mechanisms of tissue pathologies. Here, we use second harmonic generation microscopy to characterize collagen structure within bone and articular cartilage in human knees. We analyze the intensity dependence on polarization and discuss the differences between Forward and Backward images in both tissues. Focusing on articular cartilage, we observe an increase in Forward/Backward ratio from the cartilage surface to the bone. Coupling these results to numerical simulations reveals the evolution of collagen fibril diameter and spatial organization as a function of depth within cartilage.

     

Controlling quaternary structure assembly: subunit interface engineering and crystal structure of dual chain avidin

Dual chain avidin (dcAvd) is an engineered avidin form, in which two circularly permuted chicken avidin monomers are fused into one polypeptide chain. DcAvd can theoretically form two different pseudotetrameric quaternary assemblies because of symmetry at the monomer-monomer interfaces. Here, our aim was to control the assembly of the quaternary structure of dcAvd. We introduced the mutation I117C into one of the circularly permuted domains of dcAvd and scanned residues along the 1-3 subunit interface of the other domain. Interestingly, V115H resulted in a single, disulfide locked quaternary assembly of dcAvd, whereas I117H could not guide the oligomerisation process even though it stabilised the protein. The modified dcAvd forms were found to retain their characteristic pseudotetrameric state both at high and low pH, and were shown to bind D-biotin at levels comparable to that of wild-type chicken avidin. The crystal structure of dcAvd-biotin complex at 1.95 Angstroms resolution demonstrates the formation of the functional dcAvd pseudotetramer at the atomic level and reveals the molecular basis for its special properties. Altogether, our data facilitate further engineering of the biotechnologically valuable dcAvd scaffold and gives insights into how to guide the quaternary structure assembly of oligomeric proteins.     

Sequence analysis of percent G+C fraction libraries of human faecal bacterial DNA reveals a high number of Actinobacteria

Background  

The human gastrointestinal (GI) tract microbiota is characterised by an abundance of uncultured bacteria most often assigned in phyla Firmicutes and Bacteroidetes. Diversity of this microbiota, even though approached with culture independent techniques in several studies, still requires more elucidation. The main purpose of this work was to study whether the genomic percent guanine and cytosine (%G+C) -based profiling and fractioning prior to 16S rRNA gene sequence analysis reveal higher microbiota diversity, especially with high G+C bacteria suggested to be underrepresented in previous studies.     

Ligand-induced EGF receptor oligomerization is kinase-dependent and enhances internalization

The current activation model of the EGF receptor (EGFR) predicts that binding of EGF results in dimerization and oligomerization of the EGFR, leading to the allosteric activation of the intracellular tyrosine kinase. Little is known about the regulatory mechanism of receptor oligomerization. In this study, we have employed FRET between identical fluorophores (homo-FRET) to monitor the dimerization and oligomerization state of the EGFR before and after receptor activation. Our data show that, in the absence of ligand, ～40% of the EGFR molecules were present as inactive dimers or predimers. The monomer/predimer ratio was not affected by deletion of the intracellular domain. Ligand binding induced the formation of receptor oligomers, which were found in both the plasma membrane and intracellular structures. Ligand-induced oligomerization required tyrosine kinase activity and nine different tyrosine kinase substrate residues. This indicates that the binding of signaling molecules to activated EGFRs results in EGFR oligomerization. Induction of EGFR predimers or pre-oligomers using the EGFR fused to the FK506-binding protein did not affect signaling but was found to enhance EGF-induced receptor internalization. Our data show that EGFR oligomerization is the result of EGFR signaling and enhances EGFR internalization.